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README.md

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+---
+base_model: unsloth/functiongemma-270m-it
+library_name: gguf
+license: gemma
+tags:
+  - function-calling
+  - tool-use
+  - agent
+  - llama-cpp
+  - gguf
+  - unsloth
+  - llama-agent
+datasets:
+  - victor/functiongemma-agent-sft
+pipeline_tag: text-generation
+---
+
+# FunctionGemma Agent GGUF
+
+A fine-tuned version of [FunctionGemma-270M](https://huggingface.co/unsloth/functiongemma-270m-it) for agentic tool-calling tasks, converted to GGUF format for use with llama.cpp and [llama-agent](https://github.com/ggml-org/llama.cpp/tree/master/tools/agent).
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Base Model | [unsloth/functiongemma-270m-it](https://huggingface.co/unsloth/functiongemma-270m-it) |
+| Fine-tuned Model | [victor/functiongemma-agent-finetuned](https://huggingface.co/victor/functiongemma-agent-finetuned) |
+| Training Dataset | [victor/functiongemma-agent-sft](https://huggingface.co/datasets/victor/functiongemma-agent-sft) |
+| Quantization | Q4_K_M (4-bit) |
+| Parameters | 270M |
+
+## Training
+
+Fine-tuned using [Unsloth](https://github.com/unslothai/unsloth) with LoRA on HuggingFace Jobs infrastructure.
+
+**Training Configuration:**
+- LoRA rank: 128, alpha: 256
+- Epochs: 3
+- Learning rate: 2e-4
+- Batch size: 4, gradient accumulation: 2
+- Hardware: NVIDIA A100-80GB
+- Training method: SFT with `train_on_responses_only`
+
+**Dataset:** 7,500 synthetic examples covering:
+- Multi-step tool chaining (glob → read → edit)
+- Error recovery patterns
+- Clarification dialogs
+- No-tool responses
+- Parallel tool calls
+
+## Tools
+
+The model is trained on 5 tools matching llama-agent:
+
+| Tool | Description |
+|------|-------------|
+| `read_file` | Read file contents with line numbers |
+| `write_file` | Create or overwrite a file |
+| `edit_file` | Find and replace text in a file |
+| `glob` | Find files matching pattern |
+| `bash` | Execute shell command |
+
+## Usage
+
+### With llama.cpp
+
+```bash
+# Download
+wget https://huggingface.co/victor/functiongemma-agent-gguf/resolve/main/functiongemma-270m-it.Q4_K_M.gguf
+
+# Run inference
+./llama-cli -m functiongemma-270m-it.Q4_K_M.gguf -p "<start_of_turn>user
+Read the main.py file
+<end_of_turn>
+<start_of_turn>model"
+```
+
+### With llama-agent
+
+```bash
+./llama-agent -m functiongemma-270m-it.Q4_K_M.gguf
+```
+
+## Format
+
+Uses FunctionGemma's native format with `<escape>` delimiters:
+
+```
+<start_of_turn>user
+Fix the typo in config.json
+<end_of_turn>
+<start_of_turn>model
+<think>I need to find and read the config file first.</think>
+<start_function_call>call:glob{pattern:<escape>**/config.json<escape>}<end_function_call>
+<end_of_turn>
+<start_of_turn>developer
+<start_function_response>response:glob{stdout:<escape>src/config.json<escape>,stderr:<escape><escape>,exit_code:0}<end_function_response>
+<end_of_turn>
+...
+```
+
+## License
+
+This model inherits the [Gemma license](https://ai.google.dev/gemma/terms) from the base model.
+
+## Links
+
+- Training script: [victor/llama-agent-training](https://huggingface.co/victor/llama-agent-training)
+- Dataset: [victor/functiongemma-agent-sft](https://huggingface.co/datasets/victor/functiongemma-agent-sft)
+- llama-agent: [github.com/ggml-org/llama.cpp/tools/agent](https://github.com/ggml-org/llama.cpp/tree/master/tools/agent)